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Classification Framework of MapReduce Scheduling Algorithms
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DOI：10.1145/2693315.png)
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Abstract
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A MapReduce scheduling algorithm plays a critical role in managing large clusters of hardware nodes and meeting multiple quality requirements by controlling the order and distribution of users, jobs, and tasks execution. A comprehensive and structured survey of the scheduling algorithms proposed so far is presented here using a novel multidimensional classification framework. These dimensions are (i) meeting quality requirements, (ii) scheduling entities, and (iii) adapting to dynamic environments; each dimension has its own taxonomy. An empirical evaluation framework for these algorithms is recommended. This survey identifies various open issues and directions for future research.
Keywords:
MapReduce
Scheduling Algorithms
Analysis
Distributed computing
distributed data
scheduling
MapReduce
big-data
Hadoop
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